Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/43802
Title: Price uncertainty and consumer search: A structural model of consideration set formation
Authors: Mehta, N.
Rajiv, S. 
Srinivasan, K.
Keywords: Bayesian Updating
Consideration Set
Consumer Learning
Consumer Search
Econometric Estimation
Price Uncertainty
Quality Uncertainty
Structural Model
Issue Date: 2003
Source: Mehta, N.,Rajiv, S.,Srinivasan, K. (2003). Price uncertainty and consumer search: A structural model of consideration set formation. Marketing Science 22 (1) : 58-84+146. ScholarBank@NUS Repository.
Abstract: We offer an econometric framework that models consumer's consideration set formation as an outcome of her costly information search behavior. Because frequently purchased products are characterized by frequent price promotions of varying depths of discounts, a consumer faces significant uncertainty about the prices of the brands. The consumers engage in a fixed-sample search strategy that results in their discovering the posted prices of a subset of the available brands. This subset is referred to as the consumer's "consideration set." The proposed model is estimated using the scanner data set for liquid detergents. Our key empirical results are: (i) consumers zincur significant search costs to discover the posted prices of the brands; (ii) whereas in-store displays and feature ads do not influence consumers' quality perceptions of the brands, they significantly reduce search costs for observing the prices of the brands; (iii) per capita income of consumer's household significantly increases her search costs; and (iv) the consumers' price sensitivity is seriously underestimated if we were to assume that consumers get to know all the posted prices at zero cost. The proposed model is also estimated for the ketchup category to enable us to do cross-category comparisons of consumers' price search behavior.
Source Title: Marketing Science
URI: http://scholarbank.nus.edu.sg/handle/10635/43802
ISSN: 07322399
Appears in Collections:Staff Publications

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